Improvement of thermal hydrolysis rate of dichloroacetic acid using alcohol

Dichloroacetic acid (DCAA) is produced during the oxidation of trichloroethylene. It is also produced in drinking water treatment as a disinfection by-product. DCAA is a problem material, because of its toxicity. The objective of this research is to find the final products and the reaction pathway of the DCAA decomposition by hydrolysis, and to increase the hydrolysis rate. The removal of both chlorine atoms in DCAA structure was achieved with hydrolysis at around 75 degrees C, and the final products were oxalic acid and glycolic acid. The reaction pathway was the production of oxalic acid and glycolic acid from two glyoxylic acid molecules by Cannizzaro reaction after the glyoxylic acid production from dechlorination of DCAA with hydrolysis. The hydrolysis rate of DCAA was increased with the use of 90% ethanol solution as solvent. The activation energy of DCAA was about 80 kJ/mol in it, while it was around 105 kJ/mol in water.     

Prediction of effluent concentration in a wastewater treatment plant using machine learning models

Of growing amount of food waste, the integrated food waste and waste water treatment was regarded as one of the efficient modeling method. However, the load of food waste to the conventional waste treatment process might lead to the high concentration of total nitrogen(T-N) impact on the effluent water quality. The objective of this study is to establish two machine learning models—artificial neural networks(ANNs) and support vector machines(SVMs), in order to predict 1-day interval T-N concentration of effluent from a wastewater treatment plant in Ulsan, Korea. Daily water quality data and meteorological data were used and the performance of both models was evaluated in terms of the coefficient of determination(R~2), Nash–Sutcliff efficiency(NSE), relative efficiency criteria(d rel). Additionally, Latin-Hypercube one-factor-at-a-time(LH-OAT) and a pattern search algorithm were applied to sensitivity analysis and model parameter optimization, respectively. Results showed that both models could be effectively applied to the 1-day interval prediction of T-N concentration of effluent. SVM model showed a higher prediction accuracy in the training stage and similar result in the validation stage.However, the sensitivity analysis demonstrated that the ANN model was a superior model for 1-day interval T-N concentration prediction in terms of the cause-and-effect relationship between T-N concentration and modeling input values to integrated food waste and waste water treatment. This study suggested the efficient and robust nonlinear time-series modeling method for an early prediction of the water quality of integrated food waste and waste water treatment process.     

Effects of stream hydraulic conditions on foraging strategies of false dace, Pseudorasbora parva, in the lentic ecosystem

The effects of current velocity on the foraging behavior of false dace, Pseudorasbora parva, were examined in a zero velocity (stagnant) condition, and at four flow rates (5, 7, 11 and 16 cm per second). In stagnant water, the fish displayed a cruise-searching pattern, but they used a drift-feeding foraging tactic in flowing water. The shape of the transverse field of reaction field was elliptical in the stagnant condition, whereas their downward regions were restricted under the flowing conditions. The fish had a blind spot oriented directly in front of their reaction field. Although the relative swimming speed (with considering the against current velocity) increased with increasing flow velocity, the absolute search speed (ignore the against current velocity) showed about 1.2 fish body length per second at stagnant water and low flow velocity. The results of feeding rates showed stop-and wait (driff-feeding) foraging strategy is more efficient in flowing water because prey drift directly towards the fish and prey easily detected.     

Radium isotopes in the Ulsan Bay

In order to estimate the fluxes of Ra isotopes, we measured 224Ra, 226Ra, and 228Ra activities in the Ulsan Bay mixing zone. The convex upwards curvature of the plot of Ra isotope activities versus salinity for the mixing zone suggests that Ra isotopes are supplied from particles entering the mixing zone from both the river and bottom sediments. This addition increases the estuarine flux of 226Ra and 228Ra to the outer sea by factors of 15 and 95 over the flux attributable to Ra dissolved in the riverine water alone. In order to estimate the residence time of the water in Ulsan Bay, we applied a mass balance model to the distribution of 224Ra and 226Ra activities in the Ulsan Bay mixing zone with the inflow from the Taehwa River. The obtained residence times of the waters in the Ulsan Bay were estimated to be 6.8-11.4 d. The waters in the upper part of the estuary have long residence times whereas those in the lower part, in contact with the open sea, have shorter residence times. The mean residence time of the water in the Ulsan Bay was estimated to be 9.1 d.     

A taxonomy of performance influencing factors for human reliability analysis of emergency tasks

This paper introduces the process for, and the result of, the selection of performance influencing factors (PIFs) for the use in human reliability analysis (HRA) of emergency tasks in nuclear power plants. The approach taken in this study largely consists of three steps. First, a full-set PIF system is constructed from the collection and review of existing PIF taxonomies. Secondly, PIF candidates are selected from the full-set PIF system, considering the major characteristics of emergency situations and the basic criteria of PIF for use in HRA. Finally, a set of PIFs is established by structuring representative PIFs and their detailed subitems from the candidates. As a result, a set of PIFs comprised of the 11 representative PIFs and 39 subitems was developed.     

The potential implementation of green infrastructure assessment using high-resolution National Agriculture Imagery Program data for sustainable hazard mitigation

As green infrastructure gets its attention in hazard mitigation, it is necessary to improve general understanding on what makes green infrastructure important for hazard and resiliency research. To better understand how green infrastructure fits with more traditional notions of structural and nonstructural mitigation, this study examines the relationship between green infrastructure and ‘structural and nonstructural’ mitigation approaches for hazard mitigation. Also, this study discusses a new measurement of locational aspects and spatial patterns of green infrastructure by utilizing high-resolution data in urban areas, and its potential implementation in hazard mitigation. Compared to previous research using land-use land-cover datasets, the normalized difference vegetation index (NDVI) utilizing National Agriculture Imagery Program dataset provides an ability to capture green infrastructure in greater detail. A visual comparison suggests that the NDVI data are able to capture and identify more types of ‘green’ land uses in Harris County. The total green infrastructure percentages for Harris County, Texas, based on 1-m high resolution were found to be 61.5% of the area, compared to the 51.5% based on the National Land Cover Database. This study provides support for utilizing high-resolution data to establish guidelines for green infrastructure’s spatial characteristics and sustainable hazard mitigation. The outcomes of this study will be helpful in the strategic planning and implementation of green infrastructure in urban areas with hazard issues.     

Effects of environmental conditions and prey size on locomotion behaviors of planktivorous fish

The locomotion behavior of Pseudorasbora parva was observed in laboratory under various light intensity, turbidity, structural complexity and zooplankton size, focusing on swimming speed and time of search, approach, and attack. At low prey density, the satiation level affected the swimming speed only slightly. The search speed was nearly constant regardless of the satiation level to reduce the swimming energetic cost when opportunities of encountering prey were low. However, the attack and approach speeds slightly decreased with satiation. With increasing visual and swimming conditions, the approach speed increased markedly, but the search and attack speeds did not. Although the time for the approach and attack to capture a prey did not change much with decreasing swimming and visual conditions, the search time significantly increased to compensate for the decreased swimming speed.     

Accumulation of butyl- and phenyltin compounds in starfish and bivalves from the coastal environment of Korea

Triphenyltin (TPT) and tributyltin (TBT) concentrations were determined in two starfish species (Asteria pectinifera and Asterias amurensis), bivalves (Crassostrea gigas or Mytilus edulis), and seawater samples from sites around the coasts of Korea. Both TPT and TBT concentrations in starfish ranged from 8 to 1560 ng/g and from <2 to 797 ng/g as Sn on a dry weight basis, respectively. TPT concentration accounted for 75.4% and 86.4% of total phenyltin concentration in A. pectinifera and A. amurensis, respectively, while monobutyltin, a degradation product of TBT, accounted for 86.3% and 57.2% of total butyltin, respectively. Triphenyltin concentrations in A. pectinifera were significantly correlated to water and bivalve TPT concentrations, which implies that dietary uptake of TPT from contaminated prey as well as direct uptake from surrounding water contribute to TPT body residues in the starfish. Starfish could be target organisms for monitoring TPT compound in the marine environment, due to their high accumulation and low degradation capacity towards TPT.     

Levels of PCDDs and PCDFs in Korean river sediments and their detection by biomarkers

Polychlorinated dibenzo-p-dioxins (PCDDs) and dibenzofurans (PCDFs) are a group of toxic halogenated aryl hydrocarbons inducing various physiological disorders against biological organisms. Here, we investigated their levels in sediment samples taken from 12 different rivers in Korea. The levels of PCDD/PCDFs in sediment samples were expressed as concentrations and international TEQ values. Among 17 PCDD/PCDFs selected as target compounds in this study, the 1,2,3,4,7,8-HxCDD and OCDD were found in all river sediments with significant variation in various congener profiles of PCDD/PCDFs in sediments. PCDD/PCDFs could be monitored by sensitive biomarkers using insect immune system. Out of 12 river sediment samples, the biomarkers reported four spots (up, middle, and down Singil sites and Ansan) as putative contamination areas. When comparing both chemical and biological monitoring results, two methods agreed three spots of Singil as contamination areas (above 10ppt levels) as well as six river sediment samples as relatively less-contaminated areas, but differed in the results in Ansan and Miho, probably due to relative non-specificity of biomarkers. Despite some disparity between bio- and chemical monitoring results, the biomarkers can be recommended as a device warning the contamination of dioxins in the environment because of a fast and inexpensive detection method.     

市政污泥热解过程颗粒物中重金属分布

以深圳市某污水处理厂的污泥为原料,研究了污泥热解过程产生的颗粒物及其中8种重金属的分布规律.结果表明,颗粒物的生成速率分别在400~600℃和1000℃保温30min的两个区间内达到峰值.8种重金属的热挥发性由大到小依次为Cd > Zn > As > Pb > Mn > Ni > Cu > Cr,而其在颗粒物中富集能力大小顺序为Pb > As > Mn > Zn > Cd > Ni > Cr > Cu.颗粒物重金属在热解气中的体积浓度随热解过程呈上升趋势,Zn和Cd则在升温阶段（1000℃以前）达到峰值后开始降低.研究表明,污泥热解颗粒物富集的重金属超标,因而污泥热解尾气颗粒物的去除装置十分必要.